Abstract
The multiscale geographic weighted regression (MGWR) model obtains different influence scales of various variables better than the classical geographic weighted regression (GWR) model. This paper studies the price characteristics of second-hand residential transactions in Binhu New District taking advantage of the hedonic price model and MGWR model and draws the following conclusions. (1) There are obvious spatial positive correlation and spatial heterogeneity in the price of second-hand housing in Binhu New District. (2) The number of bedrooms, area, age of the house, and the distance to the nearest school have small effect on the scale, so they have strong spatial heterogeneity. The decoration status and floor are global scale variables, and their spatial heterogeneity is weak. (3) The number of bedrooms, orientation, decoration status, floor, and building structure all positively affect house prices, while area, house age, the distance to the nearest subway station, and the distance to the nearest school negatively affect house prices. Among all factors, the distance to the nearest school is the most important factor affecting house prices, followed by the number of bedrooms and then followed by the distance to the nearest subway station and area, while the orientation, floor, building structure, and decoration conditions have less impact, and the house age has the weakest impact.
Highlights
Housing is an important livelihood issue, and housing prices are a common topic of our concern
The rate of increase in housing prices is far greater than the rate of growth of the national economy in Hefei city, and there is greater pressure to purchase houses for those in need of housing
Excessive rise in housing prices will lead to some realistic social problems such as imbalances in resource allocation and excessive household income gap and will affect the healthy development of the regional economy
Summary
Housing is an important livelihood issue, and housing prices are a common topic of our concern. Binhu New District is located in the southeast of the main urban area of Hefei City, Anhui Province, China It has a planned land area of 196 square kilometers and is an important part of Hefei City’s “1331′′” urban spatial development plan. Tang et al used the GWR model to explore the impact of different influencing factors on the Shanghai community and its spatial differentiation [8]. Jinjin et al selected the second-hand housing community in Jinan and established a geographically weighted regression model to analyze the spatial distribution and impact of housing prices factor [9]. Shen et al discussed the spatial scale and spatial analysis of the influencing factors of the second-hand housing price in Beijing using the MGWR model. E results showed that location is the most important factor affecting housing prices and the influencing scale is the smallest. MGWR regression results are better than classic GWR [12]
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